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Objectives: Alpha-1-antitrypsin deficiency is a genetic disorder caused by mutations in the SERPINA1 gene encoding alpha-1-antitrypsin (AAT), the major serine protease inhibitor in plasma. Reduced AAT levels are associated with elevated risk of developing emphysema mainly due to uncontrolled activity of neutrophil elastase in the lungs. The prevalent Z-AAT mutant and many rare pathogenic AAT variants also predispose to liver disease due to their accumulation as polymeric chains in hepatocytes. Part of these polymers are secreted into the bloodstream and could represent biomarkers of intra-hepatic accumulation. Moreover, being inactive, they further lower lung protection against proteases. Aim of our study is to accurately quantify the percentage of circulating polymers (CP) in a cohort of subjects with different SERPINA1 genotypes., Methods: CP concentration was measured in plasma or Dried Blood Spot (DBS) by a sensitive sandwich ELISA based on capture by the polymer-specific 2C1 monoclonal antibody., Results: CP were significantly elevated in patients with the prevalent PI*SZ and PI*ZZ genotypes, with considerable intra-genotype variability. Notably, higher percentage of polymers was observed in association with elevated C-reactive protein. CP levels were also increased in carriers of the M malton variant, and of M procida , I, P lowell and M herleen in heterozygosity with Z-AAT., Conclusions: These findings highlight the importance of implementing CP quantification in a clinical laboratory. Indeed, the variable amount of CP in patients with the same genotype may correlate with the variable severity of the associated lung and liver diseases. Moreover, CP can reveal the polymerogenic potential of newly discovered ultrarare AAT variants., (© 2024 Walter de Gruyter GmbH, Berlin/Boston.)

Objectives: Alpha1-antitrypsin deficiency (AATD) is an inherited condition that predisposes individuals to an increased risk of developing lung and liver disease. Even though AATD is one of the most widespread inherited diseases in Caucasian populations, only a minority of affected individuals has been detected. Whereas methods have been validated for AATD testing, there is no universally-established algorithm for the detection and diagnosis of the disorder. In order to compare different methods for diagnosing AATD, we carried out a systematic review of the literature on AATD diagnostic algorithms., Methods: Complete biochemical and molecular analyses of 5,352 samples processed in our laboratory were retrospectively studied using each of the selected algorithms., Results: When applying the diagnostic algorithms to the same samples, the frequency of False Negatives varied from 1.94 to 12.9%, the frequency of True Negatives was 62.91% for each algorithm and the frequency of True Positives ranged from 24.19 to 35.15%. We, therefore, highlighted some differences among Negative Predictive Values, ranging from 0.83 to 0.97. Accordingly, the sensitivity of each algorithm ranged between 0.61 and 0.95. We also postulated 1.108 g/L as optimal AAT cut-off value, in absence of inflammatory status, which points to the possible presence of genetic AATD., Conclusions: The choice of the diagnostic algorithm has a significant impact on the correct diagnosis of AATD, which is essential for appropriate treatment and medical care. The fairly large number of possible false negative diagnoses revealed by the present paper should also warn clinicians of negative results in patients with clinically-suspected AATD., (© 2021 Alice M. Balderacchi et al., published by De Gruyter, Berlin/Boston.)